Comparison of manual and automated image analysis techniques for characterization of fission gas pores in irradiated U-Mo fuels

Charlyne A Smith; Dennis D Keiser; Brandon D Miller; Assel Aitkaliyeva

doi:10.1016/j.micron.2019.01.008

Comparison of manual and automated image analysis techniques for characterization of fission gas pores in irradiated U-Mo fuels

Micron. 2019 Apr:119:98-108. doi: 10.1016/j.micron.2019.01.008. Epub 2019 Jan 23.

Authors

Charlyne A Smith¹, Dennis D Keiser², Brandon D Miller², Assel Aitkaliyeva³

Affiliations

¹ Nuclear Engineering Program, Department of Materials Science and Engineering, University of Florida, Gainesville, FL, 32611, USA.
² Idaho National Laboratory, Idaho Falls, ID, 83415, USA.
³ Nuclear Engineering Program, Department of Materials Science and Engineering, University of Florida, Gainesville, FL, 32611, USA. Electronic address: aitkaliyeva@mse.ufl.edu.

PMID: 30708340
DOI: 10.1016/j.micron.2019.01.008

Abstract

Irradiation of low enriched uranium-molybdenum fuel results in the production and agglomeration of fission gas bubbles that can potentially lead to fuel failure. Manual point volume fraction counting in accordance with ASTME562 standard has been historically used to conduct pore size distribution analysis. While effective, the manual methodology is not efficient and therefore not feasible for the characterization of several fuel plates in a timely manner. In this contribution, ImageJ and MATLAB software were investigated as suitable alternatives to manual counting. Validation and verification were performed to show that the results are reproducible. Image analysis revealed insignificant variation of fission gas pore morphology with fission density. In addition, the results from two different sample preparation techniques - vibratory polishing and focused ion beam milling were compared. Sample preparation has more than 1% influence on the results of pore size distribution analysis. Comprehensive comparison identified vibratory polishing as the preferred method for conducting fission gas pore size distribution analysis.

Keywords: Fission gas pores; Image analysis; Pore size distribution; U-Mo fuel.

Publication types

Research Support, U.S. Gov't, Non-P.H.S.

Grants and funding

DE-AC07-05ID14517/US Department of Energy/International